
Integrate large language models into your enterprise applications with advanced strategies that drive transformation
The integration of large language models (LLMs) into enterprise applications is transforming how businesses use AI to drive smarter decisions and efficient operations. LLMs in Enterprise is your practical guide to bringing these capabilities into real-world business contexts. It demystifies the complexities of LLM deployment and provides a structured approach for enhancing decision-making and operational efficiency with AI. Starting with an introduction to the foundational concepts, the book swiftly moves on to hands-on applications focusing on real-world challenges and solutions. You’ll master data strategies and explore design patterns that streamline the optimization and deployment of LLMs in enterprise environments. From fine-tuning techniques to advanced inferencing patterns, the book equips you with a toolkit for solving complex challenges and driving AI-led innovation in business processes. By the end of this book, you’ll have a solid grasp of key LLM design patterns and how to apply them to enhance the performance and scalability of your generative AI solutions.
This book is designed for a diverse group of professionals looking to understand and implement advanced design patterns for LLMs in their enterprise applications, including AI and ML researchers exploring practical applications of LLMs, data scientists and ML engineers designing and implementing large-scale GenAI solutions, enterprise architects and technical leaders who oversee the integration of AI technologies into business processes, and software developers creating scalable GenAI-powered applications.
Auteur(s): Menshawy, Ahmed • Fahmy, Mahmoud
Editeur: Packt Publishing
Année de Publication: 2025
pages: 565
ISBN: 978-1-83620-307-0
eISBN: 978-1-83620-306-3
Cet ouvrage est présent dans ce(s) bouquet(s): Analyse des Données - Commerce International - Economie de l'Afrique - Economie de l'Energie - Economie des Inégalités